Industrial software maturity quantitative evaluation method, device, equipment, medium and product

Abstract

The invention relates to an industrial software maturity quantitative evaluation method, device and equipment, a medium and a product. The method comprises the steps that original element data of a target software product and a preset maturity quantitative evaluation model are obtained, the maturity quantitative evaluation model comprises a plurality of first-level evaluation elements representing product capacity, product application level, product market performance and product sustainability, and each first-level evaluation element comprises a plurality of second-level evaluation elements; evaluating the original element data by using the maturity quantitative evaluation model to obtain element evaluation data corresponding to each secondary evaluation element; and determining the maturity level of the target software product according to the plurality of element evaluation data. By adopting the method, the maturity of the industrial software can be comprehensively and reliably evaluated.

Description

Technical Field

[0001] This application relates to the field of software evaluation technology, and in particular to a quantitative evaluation method, apparatus, equipment, medium and product for industrial software maturity. Background Technology

[0002] Industrial software is widely used in manufacturing, energy, transportation, healthcare, and other fields, playing a crucial role in promoting the deep integration of industrialization and informatization. Industrial software is typically highly complex and specialized. To enhance user trust and acceptance of industrial software, accelerate the development of usable, user-friendly, and readily usable industrial software, and promote the high-quality development of the industrial software industry ecosystem, it is necessary to scientifically and accurately assess the maturity of industrial software.

[0003] In traditional technologies, the maturity of software process capabilities is evaluated using CMMI (Capability Maturity Model Integration).

[0004] However, current methods for quantifying and evaluating the maturity of industrial software suffer from low reliability. Summary of the Invention

[0005] Therefore, it is necessary to provide a quantitative evaluation method, apparatus, equipment, medium, and product for industrial software maturity that can comprehensively and reliably evaluate the maturity level of industrial software, addressing the aforementioned technical problems.

[0006] Firstly, this application provides a quantitative evaluation method for industrial software maturity, including:

[0007] Obtain the original element data of the target software product and the preset quantitative maturity evaluation model. The quantitative maturity evaluation model includes multiple primary evaluation elements that characterize product capabilities, product application level, product market performance and product sustainability. Each primary evaluation element includes multiple secondary evaluation elements.

[0008] The original element data were evaluated using a maturity quantitative evaluation model to obtain the element evaluation data corresponding to each secondary evaluation element;

[0009] The maturity level of the target software product is determined based on evaluation data from multiple factors.

[0010] In one embodiment, the secondary evaluation elements corresponding to product capabilities include at least one of the following: completeness of key functions, completeness of key performance, overall level of key performance, compatibility with software, compatibility with hardware, and compatibility with historical versions.

[0011] Correspondingly, the original element data includes at least one of the following: the number of key functions, the number of key performance indicators, the key performance level, the number of software compatibility indicators, the number of hardware compatibility indicators, and the number of version compatibility indicators for the target software product.

[0012] The original element data was evaluated using a maturity quantitative assessment model to obtain element evaluation data corresponding to each secondary evaluation element, including:

[0013] By using the secondary evaluation elements corresponding to product capabilities in the maturity quantitative evaluation model, the original element data and the reference element data corresponding to the reference software product are processed by ratio calculation to obtain the element evaluation data corresponding to each secondary evaluation element.

[0014] In one embodiment, the secondary evaluation elements corresponding to the product application level include at least one of the following: number of versions, average sales volume, industry coverage, degree of industry coverage, and application effectiveness.

[0015] Correspondingly, the original element data includes at least one of the following: the number of major versions of the target software product, the sales volume of each major version, the number of applicable industries, the number of industries covered, the number of user units, and the number of user units of domestic substitution.

[0016] The original element data is evaluated using a maturity quantitative assessment model to obtain element evaluation data corresponding to each secondary evaluation element, including at least one of the following:

[0017] In the quantitative maturity evaluation model, the number of major versions is proportionally amplified to obtain the element evaluation data corresponding to the number of versions.

[0018] The average sales volume of each version is calculated to obtain the factor evaluation data corresponding to the average sales volume.

[0019] The ratio of the number of applicable industries to the number of covered industries is calculated to obtain the factor evaluation data corresponding to the industry coverage rate.

[0020] The average number of user units corresponding to each covered industry is calculated to obtain the factor evaluation data corresponding to the industry coverage level.

[0021] By scaling up the number of user units using domestically produced alternatives, we can obtain the evaluation data of the factors corresponding to the application effectiveness.

[0022] In one embodiment, the secondary evaluation factors corresponding to the product market performance include at least one of profitability and sales growth.

[0023] Correspondingly, the original element data includes at least one of historical sales revenue, historical input costs, first average sales volume, and second average sales volume;

[0024] The original element data is evaluated using a maturity quantitative assessment model to obtain element evaluation data corresponding to each secondary evaluation element, including at least one of the following:

[0025] Profit is calculated based on historical sales revenue and historical input costs to obtain factor evaluation data corresponding to profitability.

[0026] The growth rate is calculated based on the first and second average sales volumes to obtain the factor evaluation data corresponding to the sales volume growth.

[0027] In one embodiment, the secondary evaluation elements corresponding to product sustainability include at least one of quality assurance, service assurance, and R&D investment.

[0028] Correspondingly, the original element data includes at least one of the following: the quality system mark, R&D qualification mark, service model mark, number of service personnel, and number of R&D personnel corresponding to the target software product;

[0029] The original element data is evaluated using a maturity quantitative assessment model to obtain element evaluation data corresponding to each secondary evaluation element, including at least one of the following:

[0030] The ratio of quality system markings and R&D qualification markings is calculated to obtain the element evaluation data corresponding to the quality assurance status.

[0031] The service mode markers are proportionally summed to obtain the element evaluation data corresponding to the service guarantee status.

[0032] We calculate the weighted sum of the number of R&D personnel to obtain the factor evaluation data corresponding to R&D investment.

[0033] In one embodiment, the maturity level of the target software product is determined based on multiple factor evaluation data, including:

[0034] The maturity evaluation data is obtained by weighted summation of the evaluation data of multiple factors.

[0035] Several core evaluation elements are determined from multiple secondary evaluation elements;

[0036] According to the preset level mapping rules, the maturity evaluation data and multiple core evaluation elements are mapped to obtain the maturity level.

[0037] Secondly, this application also provides a quantitative evaluation device for industrial software maturity, comprising:

[0038] The data acquisition module is used to acquire the original element data of the target software product and the preset quantitative maturity evaluation model. The quantitative maturity evaluation model includes multiple primary evaluation elements that characterize the product's capabilities, application level, market performance, and sustainability. Each primary evaluation element includes multiple secondary evaluation elements.

[0039] The factor evaluation module is used to evaluate the original factor data using a maturity quantitative evaluation model to obtain factor evaluation data corresponding to each secondary evaluation factor.

[0040] The maturity classification module is used to determine the maturity level of a target software product based on evaluation data from multiple factors.

[0041] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the industrial software maturity quantification evaluation method as described in the first aspect.

[0042] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the industrial software maturity quantification evaluation method as described in the first aspect.

[0043] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the industrial software maturity quantification evaluation method as described in the first aspect.

[0044] The aforementioned quantitative evaluation methods, devices, equipment, media, and products for industrial software maturity establish a quantitative evaluation model for the target software product. This model uses four primary evaluation elements—product capability, product application level, product market performance, and product sustainability—along with multiple secondary evaluation elements to evaluate the target software product and obtain its maturity level. This effectively measures the degree to which the target software product currently meets product expectations and actual application goals, providing a scientific and comprehensive evaluation of the target software product's maturity and improving the accuracy and reliability of quantitative evaluation methods for industrial software maturity. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1This is a diagram illustrating the application environment of an industrial software maturity quantification evaluation method in one embodiment.

[0047] Figure 2 This is a flowchart illustrating a quantitative evaluation method for industrial software maturity in one embodiment.

[0048] Figure 3 This is a flowchart illustrating the quantitative evaluation method for industrial software maturity in another embodiment;

[0049] Figure 4 This is a structural block diagram of an industrial software maturity quantification evaluation device in one embodiment.

[0050] Figure 5 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0052] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0053] The industrial software maturity quantification evaluation method provided in this application embodiment can be applied to, for example, Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104, or it can be located in the cloud or on another network server.

[0054] Terminal 102 is used to collect raw element data of the target software product and send it to server 104. Server 104 is used to obtain the raw element data of the target software product and a preset quantitative maturity evaluation model. The quantitative maturity evaluation model includes multiple primary evaluation elements that characterize product capabilities, product application level, product market performance, and product sustainability. Each primary evaluation element includes multiple secondary evaluation elements. The quantitative maturity evaluation model is used to evaluate the raw element data to obtain the element evaluation data corresponding to each secondary evaluation element. Based on the multiple element evaluation data, the maturity level of the target software product is determined.

[0055] Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, drones, low-altitude aircraft, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, and projection equipment. Portable wearable devices can include smartwatches, smart bracelets, and head-mounted displays. Head-mounted displays can be virtual reality (VR) devices, augmented reality (AR) devices, and smart glasses. Server 104 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services.

[0056] In one exemplary embodiment, such as Figure 2 As shown, a quantitative evaluation method for industrial software maturity is provided, which is then applied to... Figure 1 Taking server 104 as an example, the explanation includes the following steps 202 to 206. Wherein:

[0057] Step 202: Obtain the original element data of the target software product and the preset quantitative maturity evaluation model.

[0058] Among them, the quantitative maturity evaluation model includes the ability to characterize products. Product application level Product market performance and product sustainability The model comprises multiple primary evaluation elements, each of which includes multiple secondary evaluation elements. (Industrial Software Maturity Quantitative Assessment Model)

[0059] The target software product in this application embodiment is an industrial software product, specifically referring to a software product that is dedicated to or mainly used in the industrial field to improve the R&D design, production and manufacturing, operation and maintenance services, business management level of industrial enterprises and the performance of industrial equipment.

[0060] Among them, product capability mainly examines the gap between the target software product and the reference software product. The smaller the gap, the stronger the product capability of the target software product. Product application level mainly examines the update and iteration of the target software product, its application in different industry fields, and its application effectiveness in user units. Product market performance mainly examines the specific performance of the target software product in economic affairs and business transactions. Product sustainability mainly examines the quality assurance, service assurance, and R&D investment of the target software product.

[0061] Step 204: Use the maturity quantitative evaluation model to evaluate the original element data and obtain the element evaluation data corresponding to each secondary evaluation element.

[0062] The maturity quantitative evaluation model includes the evaluation methods corresponding to each secondary evaluation element.

[0063] For example, the evaluation method can be to pre-set one or more quantitative indicators, and then compare the original element data with these indicators to obtain element evaluation data.

[0064] For example, the evaluation method can also be to construct a hierarchical structure, decompose each secondary evaluation element into multiple levels, and then determine the relative importance and weight of each secondary evaluation element through expert scoring and comparison, and finally comprehensively calculate the element evaluation data.

[0065] Step 206: Determine the maturity level of the target software product based on the evaluation data of multiple factors.

[0066] For example, the maturity level of a target software product can be determined by assigning weights to the evaluation data of each element and then using a weighted average; or, a fuzzy matrix can be used to describe the membership degree between each primary and secondary evaluation element and the maturity level, and the fuzzy comprehensive evaluation vector can be obtained based on the membership degree to finally determine the maturity level.

[0067] In some embodiments, the method can also generate evaluation conclusions based on maturity levels, and propose evaluation strengths, evaluation weaknesses, and improvement directions for the target software product in the evaluation conclusions.

[0068] The aforementioned quantitative evaluation method for industrial software maturity establishes a quantitative evaluation model for the target software product. This model uses four primary evaluation elements—product capability, product application level, product market performance, and product sustainability—along with multiple secondary evaluation elements to evaluate the target software product and obtain its maturity level. This effectively measures the degree to which the target software product currently meets product expectations and actual application goals, providing a scientific and comprehensive evaluation of the target software product's maturity and improving the accuracy and reliability of the quantitative evaluation method for industrial software maturity.

[0069] In one exemplary embodiment, based on Figure 2 In the illustrated embodiment, the secondary evaluation elements corresponding to product capabilities include at least one of the following: completeness of key functions, completeness of key performance, overall level of key performance, compatibility with software, compatibility with hardware, and compatibility with historical versions.

[0070] Correspondingly, the original element data includes at least one of the following: the number of key functions, the number of key performance indicators, the key performance level, the number of software compatibility indicators, the number of hardware compatibility indicators, and the number of version compatibility indicators for the target software product.

[0071] The original element data is evaluated using a maturity quantitative evaluation model to obtain the element evaluation data corresponding to each secondary evaluation element. This includes: using the secondary evaluation elements corresponding to product capabilities in the maturity quantitative evaluation model, the ratio of the original element data and the reference element data corresponding to the reference software product is calculated to obtain the element evaluation data corresponding to each secondary evaluation element.

[0072] Among them, the reference software product refers to one or more software products of the same type as the target software product that are in a leading position and whose functions and performance are widely recognized in the industry; the reference element data refers to the original element data corresponding to the reference software product.

[0073] Specifically, key functions refer to core functions that are generally applicable to users, as well as major functions that represent software development trends. Completeness of key functions. This involves benchmarking against reference software products to assess the extent to which the target software product has achieved its key functionalities, which can be expressed as:

[0074]

[0075] in, This indicates the number of key functions of the reference software product in the reference element data. This indicates the number of key functions corresponding to the target software product in the original feature data.

[0076] Key performance refers to the core performance characteristics that affect the overall quality of software. Completeness of key performance indicators. The degree to which the target software product has achieved key performance characteristics is calculated by benchmarking against reference software products, and can be expressed as:

[0077]

[0078] in, This indicates the number of key performance indicators (KPIs) achieved in the reference software product. This indicates the number of key performance indicators for the target software product.

[0079] Overall level of key performance The target software product's achieved key performance level is calculated by comparing it with that of a reference software product. This can be expressed as:

[0080] ,

[0081] in, This indicates the number of key performance indicators for the target software product. 1 indicates a critical performance level. This indicates the number of key performance levels that the target software product has achieved at level i. This represents the weight of the i-th level. For example, =3, the three levels represent domestically advanced, internationally advanced, and internationally leading, respectively, and the weight value corresponding to each level can be expressed as:

[0082] Compatible software capabilities This involves comparing the number of domestically developed basic software programs that the target software product should be compatible with, as well as upstream and downstream software programs from both domestic and international sources, to calculate the number of compatible programs and their application extent.

[0083] ,

[0084] in, This indicates the number of software programs that the reference software product should be compatible with, i.e., the number of software programs that should be compatible with it. 2 indicates the verification level. This indicates the number of verification levels (i-th) that the target software product is compatible with. This represents the weight of the i-th verification level, for example, =3, with verification levels of simulation verification, user verification, and user practice.

[0085] Compatible hardware capabilities This involves comparing the target software product with domestic and international CPUs that it should be compatible with, and calculating the number of CPUs it is already compatible with and the extent of its application.

[0086]

[0087] in, This indicates the number of hardware components that the reference software product should be compatible with, i.e., the number of hardware components it should be compatible with. 2 indicates the verification level. This indicates the number of verification levels (i-th) that the target software product should be compatible with in the hardware. This represents the weight of the i-th verification level. For example, =3, with verification levels of simulation verification, user verification, and user practice.

[0088] Compatible with historical versions This involves calculating and evaluating the compatibility of the current, cumulatively released, and contracted versions of the target software product with previous versions.

[0089]

[0090] in, This indicates the current cumulative number of major versions released with sales contracts, with a maximum value of 10. Version compatibility count indicates the number of historical versions that the target software product version can be compatible with, with a maximum value of 10.

[0091] In this embodiment of the application, the target software product is evaluated using various secondary evaluation elements that characterize product capabilities. This ensures that the evaluation method can scientifically measure the gap between the target software product and the reference software product, thereby improving the accuracy of the quantitative evaluation method for industrial software maturity.

[0092] In one exemplary embodiment, based on Figure 2 The illustrated embodiment shows that the secondary evaluation elements corresponding to the product application level include at least one of the following: number of versions, average sales volume, industry coverage, degree of industry coverage, and application effectiveness.

[0093] Correspondingly, the original element data includes at least one of the following: the number of major versions of the target software product, the sales volume of each major version, the number of applicable industries, the number of industries covered, the number of user units, and the number of user units for domestic substitution.

[0094] The original element data is evaluated using a maturity quantitative assessment model to obtain element evaluation data corresponding to each secondary evaluation element, including performing at least one of the following 1-5 in the maturity quantitative assessment model:

[0095] 1. Calculate the number of major versions proportionally to obtain the element evaluation data corresponding to the number of versions.

[0096] Among them, the number of versions This refers to the cumulative number of major versions of the target software product that have been released and have sales contracts:

[0097]

[0098] in, This indicates the current cumulative number of major versions that have been released and have sales contracts, with a maximum value of 10.

[0099] 2. Calculate the average sales volume for each version to obtain the factor evaluation data corresponding to the average sales volume.

[0100] Among them, average sales volume This involves statistically analyzing the sales volume of each major version release of the target software product and calculating the average sales volume for each version.

[0101]

[0102] in, This indicates the current cumulative number of major versions that have been released and have sales contracts, with a maximum value of 10. This represents the current cumulative sales volume of the i-th major version.

[0103] 3. Calculate the ratio between the number of applicable industries and the number of covered industries to obtain the factor evaluation data corresponding to the industry coverage rate.

[0104] Among them, industry coverage This refers to the extent to which the target software product has covered various industries.

[0105]

[0106] in, This indicates the number of industries in which the target software product is applicable. This indicates the number of industries covered by the target software product, i.e., the number of industries already covered. For industries to be covered by the target software product, there must already be sales contracts in those industries, and a certain scale of industry-specific components, databases, etc., must have been developed.

[0107] 4. Calculate the average number of user units corresponding to each covered industry to obtain the factor evaluation data corresponding to the industry coverage level.

[0108] Among them, industry coverage This involves assessing the extent of industry coverage by statistically analyzing the number of user units within the target software product's existing industry coverage. This can be represented as:

[0109]

[0110] in, This represents the number of user units in the i-th industry that the target software product has covered. This indicates the number of industries covered by the target software product. If the value is greater than 100, it will be calculated as 100.

[0111] 5. Calculate the number of user units using domestically produced alternatives by scaling up the calculations to obtain the element evaluation data corresponding to the application effectiveness.

[0112] Among them, application effectiveness This involves statistically analyzing real-world application cases of the product to assess its domestic substitution capabilities within user organizations. This can be represented as follows:

[0113]

[0114] in, The number of user units that have been replaced by domestically produced software indicates the number of user units for which the target software product has been replaced by domestically produced software. The value is less than 100.

[0115] In this embodiment, the target software product is evaluated using various secondary evaluation elements that characterize the application level of the product. This ensures that the evaluation method can scientifically measure the development of the target software product and ensures the reliability of the element evaluation data.

[0116] In one exemplary embodiment, based on Figure 2 In the illustrated embodiment, the secondary evaluation factors corresponding to the product market performance include at least one of profitability and sales growth; correspondingly, the original factor data includes at least one of historical sales revenue, historical input costs, first average sales volume, and second average sales volume.

[0117] The original element data is evaluated using a quantitative maturity assessment model to obtain element evaluation data corresponding to each secondary evaluation element, including performing at least one of the following in the quantitative maturity assessment model:

[0118] 1. Calculate profits based on historical sales revenue and historical input costs to obtain factor evaluation data corresponding to profitability.

[0119] Among them, profitability To assess the total profit generated when the historical sales revenue of a target software product exceeds its historical investment costs, the profit calculation can be expressed as follows:

[0120]

[0121] in, This represents the historical sales revenue of the target software product. This represents the historical investment cost of the target software product. The value is less than 100.

[0122] 2. Calculate the growth rate based on the first and second average sales volumes to obtain the factor evaluation data corresponding to the sales volume growth.

[0123] Among them, sales volume growth This involves assessing the sales changes of the target software product in its target market by statistically analyzing its sales volume over the past five years. The growth rate calculation process can be expressed as follows:

[0124]

[0125] Among them, the first average sales volume This represents the average sales volume of the target software product in its target market over the past three years, followed by the second average sales volume. This indicates the average sales volume of the target software product in its target market over the past five years. The value is less than 100.

[0126] In this embodiment, the target software product is evaluated using various secondary evaluation elements that characterize the product's market performance. This ensures that the evaluation method takes into account the product's commercial sustainability and that the evaluation data is practical and comprehensive.

[0127] In one exemplary embodiment, based on Figure 2 In the illustrated embodiment, the secondary evaluation elements corresponding to product sustainability include at least one of quality assurance, service assurance, and R&D investment; correspondingly, the original element data includes at least one of the following: quality system label, R&D qualification label, service model label, number of service personnel, and number of R&D personnel corresponding to the target software product.

[0128] The original element data is evaluated using a quantitative maturity assessment model to obtain element evaluation data corresponding to each secondary evaluation element, including performing at least one of the following in the quantitative maturity assessment model:

[0129] 1. Calculate the ratio summation of quality system markings and R&D qualification markings to obtain the element evaluation data corresponding to the quality assurance status.

[0130] Among them, quality assurance situation The assessment is conducted based on the target software product's adherence to the quality system during its development process and the development qualifications of the assessed entity.

[0131]

[0132] Wherein, G is the quality system marker, indicating the quality system followed in the development process of the target software product. If the quality system is not followed, G=0; if the requirements of GB / T19001 or GJB 9001C quality system are followed, G=6. K is the R&D qualification marker, indicating the software R&D capability of the target software product R&D unit. Wherein, if the target software product R&D unit has obtained GJB5000B or CMMI Level 2 qualification, K=1; Level 3 qualification, K=2; Level 4 qualification, K=3; and Level 5 qualification, K=4.

[0133] 2. Perform proportional summation calculations on the service mode markers to obtain the element evaluation data corresponding to the service guarantee status.

[0134] Among them, service guarantee situation This indicates the service guarantee model and the number of service personnel for the target software product:

[0135]

[0136] in, This is a service mode identifier, indicating original manufacturer service within the product warranty service model. If original manufacturer service is supported, then... =l, otherwise =0. This is a marker for another service model, indicating the agency service within the product guarantee service model. If agency services are supported, then... =1, otherwise =0. Indicates the number of service personnel. If... If the value is greater than 100, it will be calculated as 100.

[0137] 3. Perform a weighted summation calculation on the number of R&D personnel to obtain the element evaluation data corresponding to the R&D investment.

[0138] Among them, R&D investment This involves calculating the investment in the R&D personnel of the target software product. The number of R&D personnel includes the number of technical leaders, key R&D personnel, and new employees. (R&D investment details) It can be represented as:

[0139]

[0140] This represents the number of R&D personnel for the target software product, i.e., the total number of personnel involved in R&D. This represents the number of technical leaders in the R&D team for the target software product. =4, This represents the number of key R&D personnel invested in the development of the target software product. =2, This indicates the number of new employees recruited for the development of the target software product in the past three years. =1. If If the value is greater than 100, it will be calculated as 100.

[0141] In this embodiment of the application, the target software product is evaluated by using various secondary evaluation elements that characterize the product's sustainability, which can proactively assess the target software product's vitality and risk resistance.

[0142] In one exemplary embodiment, based on Figure 2 The embodiment shown describes a method for determining the maturity level of a target software product based on multiple factor evaluation data. This includes: performing a weighted summation of the multiple factor evaluation data to obtain maturity evaluation data; determining multiple core evaluation factors from multiple secondary evaluation factors; and mapping the maturity evaluation data and the multiple core evaluation factors according to a preset level mapping rule to obtain the maturity level.

[0143] The maturity evaluation data is calculated by weighting and summing the evaluation data of each element and their corresponding weights. Each primary evaluation element has a score. Includes a weighted sum of the scores for each of the corresponding secondary evaluation elements:

[0144]

[0145] In the formula, The element evaluation data corresponding to the j-th secondary evaluation element; This refers to the number of secondary evaluation elements within the current primary evaluation elements; The weight is the weight corresponding to the j-th secondary evaluation element.

[0146] Maturity assessment data The weighted sum of the scores for the four primary evaluation elements in the above embodiment is as follows:

[0147]

[0148] In the formula: The score for the kth primary evaluation element; denoted as the weight of the k-th primary evaluation element.

[0149] For example, the weights assigned to each primary evaluation element and secondary evaluation element can be shown in Table 1.

[0150] Table 1 Weight Allocation of Primary and Secondary Evaluation Elements

[0151]

[0152] In this embodiment, the completeness of key functions, the completeness of key performance, the overall level of key performance, application effectiveness, profitability, and quality assurance are used as core evaluation elements. Mapping maturity evaluation data to multiple core evaluation elements means that the maturity evaluation data exceeds the minimum score required for the grade, and the evaluation data for each core evaluation element also exceeds the minimum score required for the grade. If any maturity evaluation data is less than or equal to the minimum score required for the grade, or if any core evaluation element's evaluation data is less than or equal to the minimum score required for the grade, then the grade is considered not met.

[0153] For example, the level mapping rules can be shown in Table 2.

[0154] Table 2. Level Mapping Rules

[0155]

[0156] In this embodiment, the maturity level is determined based on both maturity evaluation data and core element requirement scores, which can improve the accuracy, scientificity, and objectivity of the quantitative evaluation method for industrial software maturity.

[0157] In one exemplary embodiment, such as Figure 3 As shown, a quantitative evaluation method for industrial software maturity is provided, which includes the following steps 301 to 305. Wherein:

[0158] Step 301: Obtain the original element data of the target software product and the preset quantitative maturity evaluation model.

[0159] The maturity quantitative evaluation model includes multiple primary evaluation elements that characterize product capabilities, product application level, product market performance, and product sustainability. Each primary evaluation element includes multiple secondary evaluation elements.

[0160] Step 302: Use the maturity quantitative evaluation model to evaluate the original element data and obtain the element evaluation data corresponding to each secondary evaluation element.

[0161] The secondary evaluation elements corresponding to product capabilities include at least one of the following: completeness of key functions, completeness of key performance, overall level of key performance, compatibility with software, compatibility with hardware, and compatibility with historical versions. Correspondingly, the original element data includes at least one of the following: number of key functions, number of key performance indicators, key performance level, number of software compatible features, number of hardware compatible features, and number of version compatible features for the target software product. Step 302 may further include: using the secondary evaluation elements corresponding to product capabilities in the maturity quantitative evaluation model, performing proportional calculations on the original element data and the reference element data corresponding to the reference software product to obtain the element evaluation data corresponding to each secondary evaluation element.

[0162] The secondary evaluation elements corresponding to the product application level include at least one of the following: number of versions, average sales volume, industry coverage rate, industry coverage degree, and application effectiveness. Correspondingly, the original element data includes at least one of the following: number of major versions corresponding to the target software product, sales volume corresponding to each major version, number of applicable industries, number of covered industries, number of user units, and number of user units using domestic substitution. Step 302 may further include: in the maturity quantitative evaluation model, proportionally scaling up the number of major versions to obtain the element evaluation data corresponding to the number of versions; calculating the average sales volume corresponding to each major version to obtain the element evaluation data corresponding to the average sales volume; proportionally calculating the number of applicable industries and the number of covered industries to obtain the element evaluation data corresponding to the industry coverage rate; calculating the average number of user units corresponding to each covered industry to obtain the element evaluation data corresponding to the industry coverage degree; and proportionally scaling up the number of user units using domestic substitution to obtain the element evaluation data corresponding to the application effectiveness.

[0163] The secondary evaluation factors corresponding to product market performance include at least one of profitability and sales volume growth; correspondingly, the original factor data includes at least one of historical sales revenue, historical input costs, first average sales volume, and second average sales volume. Step 302 may further include: calculating profit based on historical sales revenue and historical input costs to obtain factor evaluation data corresponding to profitability; and calculating the growth rate based on first average sales volume and second average sales volume to obtain factor evaluation data corresponding to sales volume growth.

[0164] The secondary evaluation elements corresponding to product sustainability include at least one of quality assurance, service assurance, and R&D investment. Correspondingly, the original element data includes at least one of the following: quality system label, R&D qualification label, service model label, number of service personnel, and number of R&D personnel for the target software product. Step 302 may further include: calculating the proportional summation of the quality system label and R&D qualification label to obtain the element evaluation data corresponding to quality assurance; calculating the proportional summation of the service model label to obtain the element evaluation data corresponding to service assurance; and calculating the weighted summation of the number of R&D personnel to obtain the element evaluation data corresponding to R&D investment.

[0165] Step 303: Perform weighted summation on the evaluation data of multiple elements to obtain maturity evaluation data.

[0166] Step 304: Determine multiple core evaluation elements from multiple secondary evaluation elements.

[0167] Step 305: According to the preset level mapping rules, the maturity evaluation data and multiple core evaluation elements are mapped to obtain the maturity level.

[0168] It should be understood that although the steps in the flowcharts of the above embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the above embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0169] Based on the same inventive concept, this application also provides an industrial software maturity quantification evaluation device for implementing the aforementioned industrial software maturity quantification evaluation method. The solution provided by this device is similar to the implementation scheme described in the above method; therefore, the specific limitations of one or more industrial software maturity quantification evaluation device embodiments provided below can be found in the limitations of the industrial software maturity quantification evaluation method described above, and will not be repeated here.

[0170] In one exemplary embodiment, such as Figure 4 As shown, an industrial software maturity quantification and evaluation device is provided, including: a data acquisition module 402, an element evaluation module 404, and a level classification module 406, wherein:

[0171] The data acquisition module 402 is used to acquire the original element data of the target software product and the preset quantitative maturity evaluation model. The quantitative maturity evaluation model includes multiple primary evaluation elements that characterize the product's capabilities, application level, market performance, and sustainability. Each primary evaluation element includes multiple secondary evaluation elements.

[0172] The element evaluation module 404 is used to evaluate the original element data using a maturity quantitative evaluation model to obtain the element evaluation data corresponding to each secondary evaluation element.

[0173] The grading module 406 is used to determine the maturity level of the target software product based on evaluation data from multiple factors.

[0174] In one embodiment, the secondary evaluation elements corresponding to product capabilities include at least one of key function completeness, key performance completeness, overall key performance level, compatible software capability, compatible hardware capability, and compatible historical version capability; correspondingly, the original element data includes at least one of the number of key functions, number of key performances, key performance level, number of software compatibility, number of hardware compatibility, and number of version compatibility corresponding to the target software product; the element evaluation module 404 is also used to use the secondary evaluation elements corresponding to product capabilities in the maturity quantitative evaluation model to perform proportional calculation processing on the original element data and the reference element data corresponding to the reference software product to obtain the element evaluation data corresponding to each secondary evaluation element.

[0175] In one embodiment, the secondary evaluation elements corresponding to the product application level include at least one of the following: number of versions, average sales volume, industry coverage rate, industry coverage degree, and application effectiveness. Correspondingly, the original element data includes at least one of the following: number of major versions corresponding to the target software product, sales volume corresponding to each major version, number of applicable industries, number of covered industries, number of user units, and number of user units replaced by domestic alternatives. The element evaluation module 404 is also used in the maturity quantitative evaluation model to perform proportional amplification calculation on the number of major versions to obtain element evaluation data corresponding to the number of versions; to calculate the average of the sales volume corresponding to each major version to obtain element evaluation data corresponding to the average sales volume; to calculate the ratio between the number of applicable industries and the number of covered industries to obtain element evaluation data corresponding to the industry coverage rate; to calculate the average of the number of user units corresponding to each covered industry to obtain element evaluation data corresponding to the industry coverage degree; and to perform proportional amplification calculation on the number of user units replaced by domestic alternatives to obtain element evaluation data corresponding to the application effectiveness.

[0176] In one embodiment, the secondary evaluation elements corresponding to the product market performance include at least one of profitability and sales growth; correspondingly, the original element data includes at least one of historical sales revenue, historical input costs, first average sales volume, and second average sales volume; the element evaluation module 404 is also used to calculate profits based on historical sales revenue and historical input costs to obtain element evaluation data corresponding to profitability; and to calculate the growth rate based on the first average sales volume and second average sales volume to obtain element evaluation data corresponding to sales growth.

[0177] In one embodiment, the secondary evaluation elements corresponding to product sustainability include at least one of quality assurance, service assurance, and R&D investment. Correspondingly, the original element data includes at least one of the following: quality system label, R&D qualification label, service model label, number of service personnel, and number of R&D personnel corresponding to the target software product. The element evaluation module 404 is also used to perform a proportional summation calculation on the quality system label and the R&D qualification label to obtain the element evaluation data corresponding to the quality assurance; to perform a proportional summation calculation on the service model label to obtain the element evaluation data corresponding to the service assurance; and to perform a weighted summation calculation on the number of R&D personnel to obtain the element evaluation data corresponding to the R&D investment.

[0178] In one embodiment, the grading module 406 is further used to perform weighted summation processing on multiple element evaluation data to obtain maturity evaluation data; determine multiple core evaluation elements from multiple secondary evaluation elements; and perform mapping processing on the maturity evaluation data and multiple core evaluation elements according to preset grading mapping rules to obtain maturity levels.

[0179] Each module in the aforementioned industrial software maturity quantification and evaluation device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, so that the processor can call and execute the operations corresponding to each module.

[0180] In one exemplary embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 5 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs stored in the non-volatile storage media. The database stores raw data. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements an industrial software maturity metric evaluation method.

[0181] Those skilled in the art will understand that Figure 5The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0182] In one exemplary embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0183] In one exemplary embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above-described method embodiments.

[0184] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0185] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0186] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0187] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0188] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A quantitative evaluation method for industrial software maturity, characterized in that, The method includes: Obtain the original element data of the target software product and the preset quantitative maturity evaluation model. The quantitative maturity evaluation model includes multiple primary evaluation elements that characterize product capabilities, product application level, product market performance and product sustainability. Each primary evaluation element includes multiple secondary evaluation elements. The original element data is evaluated using the maturity quantitative evaluation model to obtain element evaluation data corresponding to each of the secondary evaluation elements; The maturity level of the target software product is determined based on the evaluation data of multiple factors.

2. The method according to claim 1, characterized in that, The secondary evaluation elements corresponding to the product capabilities include at least one of the following: completeness of key functions, completeness of key performance, overall level of key performance, compatibility with software, compatibility with hardware, and compatibility with historical versions. Correspondingly, the original element data includes at least one of the following: the number of key functions, the number of key performance indicators, the key performance level, the number of software compatibility indicators, the number of hardware compatibility indicators, and the number of version compatibility indicators corresponding to the target software product. The process of evaluating the original element data using the maturity quantitative evaluation model to obtain element evaluation data corresponding to each of the secondary evaluation elements includes: Using the secondary evaluation elements corresponding to the product capabilities in the maturity quantitative evaluation model, the original element data and the reference element data corresponding to the reference software product are processed by ratio calculation to obtain the element evaluation data corresponding to each of the secondary evaluation elements.

3. The method according to claim 1, characterized in that, The secondary evaluation elements corresponding to the product application level include at least one of the following: number of versions, average sales volume, industry coverage, degree of industry coverage, and application effectiveness. Correspondingly, the original element data includes at least one of the following: the number of major versions of the target software product, the sales volume of each major version, the number of applicable industries, the number of industries covered, the number of user units, and the number of user units for domestic substitution. The evaluation of the original element data using the maturity quantitative evaluation model to obtain element evaluation data corresponding to each of the secondary evaluation elements includes at least one of the following: In the quantitative maturity evaluation model, the number of major versions is proportionally amplified to obtain the element evaluation data corresponding to the number of versions; The average sales volume of each version is calculated to obtain the factor evaluation data corresponding to the average sales volume. The ratio of the number of applicable industries to the number of covered industries is calculated to obtain the element evaluation data corresponding to the industry coverage rate. The average number of user units corresponding to each covered industry is calculated to obtain the element evaluation data corresponding to the industry coverage level; The number of domestically produced replacement user units is proportionally amplified to obtain the element evaluation data corresponding to the application effectiveness.

4. The method according to claim 1, characterized in that, The secondary evaluation factors corresponding to the product market performance include at least one of profitability and sales growth. Correspondingly, the original element data includes at least one of historical sales revenue, historical input costs, first average sales volume, and second average sales volume; The evaluation of the original element data using the maturity quantitative evaluation model to obtain element evaluation data corresponding to each of the secondary evaluation elements includes at least one of the following: Profit is calculated based on the historical sales revenue and historical input costs to obtain the factor evaluation data corresponding to the profitability situation; The growth rate is calculated based on the first average sales volume and the second average sales volume to obtain the factor evaluation data corresponding to the sales volume growth.

5. The method according to claim 1, characterized in that, The secondary evaluation elements for product sustainability include at least one of the following: quality assurance, service assurance, and R&D investment. Correspondingly, the original element data includes at least one of the following: quality system mark, R&D qualification mark, service model mark, number of service personnel, and number of R&D personnel corresponding to the target software product; The evaluation of the original element data using the maturity quantitative evaluation model to obtain element evaluation data corresponding to each of the secondary evaluation elements includes at least one of the following: The quality system markers and R&D qualification markers are proportionally summed to obtain the element evaluation data corresponding to the quality assurance status. The service mode markers are proportionally summed to obtain the element evaluation data corresponding to the service guarantee status; The number of R&D personnel is weighted and summed to obtain the element evaluation data corresponding to the R&D investment.

6. The method according to any one of claims 1-5, characterized in that, The step of determining the maturity level of the target software product based on multiple evaluation data elements includes: The maturity evaluation data is obtained by performing a weighted summation on the evaluation data of multiple elements. Multiple core evaluation elements are determined from the multiple secondary evaluation elements; According to the preset level mapping rules, the maturity evaluation data and multiple core evaluation elements are mapped to obtain the maturity level.

7. A quantitative evaluation device for industrial software maturity, characterized in that, The device includes: The data acquisition module is used to acquire the original element data of the target software product and the preset quantitative maturity evaluation model. The quantitative maturity evaluation model includes multiple primary evaluation elements that characterize product capabilities, product application level, product market performance and product sustainability. Each primary evaluation element includes multiple secondary evaluation elements. The element evaluation module is used to evaluate the original element data using the maturity quantitative evaluation model to obtain element evaluation data corresponding to each of the secondary evaluation elements; The grading module is used to determine the maturity level of the target software product based on the evaluation data of multiple elements.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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